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ThinkStack

Supply Chain Transformation

Demand Planning & Forecasting

AI-assisted forecasting across history, seasonality, promotions, geography and business rules.

Discuss a Transformation

The opportunity

Demand Planning & Forecasting

Forecasting is the decision every other supply-chain decision inherits. When it is wrong the cost cascades — expedited freight, lost sales, markdowns and cash trapped in the wrong stock — yet most enterprises still forecast in monthly cycles against a single aggregate that hides the variation where the money actually moves. ThinkStack applies AI to forecast at the level decisions are made — SKU, store, channel and region — reading history, seasonality, promotions and near-term signals together, and attaching a confidence level so planners know exactly where to trust the number and where to intervene. The objective is not a marginally lower error statistic; it is a demand plan the whole organisation can commit to.

What we build

Capabilities that change the economics of the work.

  • SKU, store and regional forecasting

    Granular forecasts at the level decisions are actually made, not a single aggregate that hides local reality.

  • Seasonality and promotion modelling

    Separates baseline demand from campaign and seasonal lift so promotions are planned on evidence, not instinct.

  • Demand sensing

    Reads near-term signals — orders, point-of-sale, weather, events — to adjust short-horizon plans while there is still time to act.

  • Anomaly and bias detection

    Flags forecasts that drift from reality and the systematic biases that erode trust in the numbers.

  • Forecast confidence scoring

    Attaches a confidence level to every forecast so planners know where to lean on the model and where to intervene.

  • Forecasting copilots

    Lets planners interrogate and adjust forecasts in plain language, with the model explaining its reasoning.

How we work

From workflow to working AI — with value at each step.

01

Discover & map

We study how the work actually happens, the decisions that drive it and where value is lost.

02

Redesign

We decide what stays human, where AI assists and what agents execute — with controls by design.

03

Build & integrate

We develop the AI and software and connect it to your systems of record.

04

Deploy

We launch into the flow of work with governance, then support adoption.

05

Optimise

We measure outcomes and keep improving — because value compounds after go-live.

FAQ

What should AI change inside your business?

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